scholarly journals EARLY PREDICTION OF ACUTE KIDNEY INJURY AFTER ACUTE MYOCARDIAL INFARCTION BY A CLINICAL RISK SCORE

2016 ◽  
Vol 67 (13) ◽  
pp. 478 ◽  
Author(s):  
Katsuomi Iwakura ◽  
Atsunori Okamura ◽  
Yasushi Koyama ◽  
Koichi Inoue ◽  
Hiroyuki Nagai ◽  
...  
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
William T. McBride ◽  
Mary Jo Kurth ◽  
Gavin McLean ◽  
Anna Domanska ◽  
John V. Lamont ◽  
...  

AbstractAcute kidney injury (AKI) following cardiac surgery significantly increases morbidity and mortality risks. Improving existing clinical methods of identifying patients at risk of perioperative AKI may advance management and treatment options. This study investigated whether a combination of biomarkers and clinical factors pre and post cardiac surgery could stratify patients at risk of developing AKI. Patients (n = 401) consecutively scheduled for elective cardiac surgery were prospectively studied. Clinical data was recorded and blood samples were tested for 31 biomarkers. Areas under receiver operating characteristic (AUROCs) were generated for biomarkers pre and postoperatively to stratify patients at risk of AKI. Preoperatively sTNFR1 had the highest predictive ability to identify risk of developing AKI postoperatively (AUROC 0.748). Postoperatively a combination of H-FABP, midkine and sTNFR2 had the highest predictive ability to identify AKI risk (AUROC 0.836). Preoperative clinical risk factors included patient age, body mass index and diabetes. Perioperative factors included cardio pulmonary bypass, cross-clamp and operation times, intra-aortic balloon pump, blood products and resternotomy. Combining biomarker risk score (BRS) with clinical risk score (CRS) enabled pre and postoperative assignment of patients to AKI risk categories. Combining BRS with CRS will allow better management of cardiac patients at risk of developing AKI.


2013 ◽  
Vol 27 (6) ◽  
pp. 1158-1166 ◽  
Author(s):  
Won Ho Kim ◽  
Sangmin M. Lee ◽  
Ji Won Choi ◽  
Eun Hee Kim ◽  
Jong Hwan Lee ◽  
...  

2021 ◽  
Vol 35 ◽  
pp. 100826
Author(s):  
Ryota Kosaki ◽  
Kohei Wakabayashi ◽  
Shunya Sato ◽  
Hideaki Tanaka ◽  
Kunihiro Ogura ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Side Gao ◽  
Qingbo Liu ◽  
Hui Chen ◽  
Mengyue Yu ◽  
Hongwei Li

Abstract Background Acute hyperglycemia has been recognized as a robust predictor for occurrence of acute kidney injury (AKI) in nondiabetic patients with acute myocardial infarction (AMI), however, its discriminatory ability for AKI is unclear in diabetic patients after an AMI. Here, we investigated whether stress hyperglycemia ratio (SHR), a novel index with the combined evaluation of acute and chronic glycemic levels, may have a better predictive value of AKI as compared with admission glycemia alone in diabetic patients following AMI. Methods SHR was calculated with admission blood glucose (ABG) divided by the glycated hemoglobin-derived estimated average glucose. A total of 1215 diabetic patients with AMI were enrolled and divided according to SHR tertiles. Baseline characteristics and outcomes were compared. The primary endpoint was AKI and secondary endpoints included all-cause death and cardiogenic shock during hospitalization. The logistic regression analysis was performed to identify potential risk factors. Accuracy was defined with area under the curve (AUC) by a receiver-operating characteristic (ROC) curve analysis. Results In AMI patients with diabetes, the incidence of AKI (4.4%, 7.8%, 13.0%; p < 0.001), all-cause death (2.7%, 3.6%, 6.4%; p = 0.027) and cardiogenic shock (4.9%, 7.6%, 11.6%; p = 0.002) all increased with the rising tertile levels of SHR. After multivariate adjustment, elevated SHR was significantly associated with an increased risk of AKI (odds ratio 3.18, 95% confidence interval: 1.99–5.09, p < 0.001) while ABG was no longer a risk factor of AKI. The SHR was also strongly related to the AKI risk in subgroups of patients. At ROC analysis, SHR accurately predicted AKI in overall (AUC 0.64) and a risk model consisted of SHR, left ventricular ejection fraction, N-terminal B-type natriuretic peptide, and estimated glomerular filtration rate (eGFR) yielded a superior predictive value (AUC 0.83) for AKI. Conclusion The novel index SHR is a better predictor of AKI and in-hospital mortality and morbidity than admission glycemia in AMI patients with diabetes.


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